我如何确保 spatstat::owin(poly=<polygon> ) 没有“负区域”

Question

I am a new user of the R spatstat package and am having problems creating a polygonal observation window with owin(). Code follows:

library("maps")
library ("sp")` 
library("spatstat")
mass.map <- map("state", "massachusetts:main", fill=T) # This returns a data frame includding x and y components that form a polygon of massachusetts mainland`

mass.win <- owin(poly=data.frame(x=mass.map$x, y=mass.map$y)

Error in if (w.area < 0) stop(paste("Area of polygon is negative -", "maybe traversed in >wrong direction?")) : missing value where TRUE/FALSE needed

I tried things like reversing the order of the polygon and got same error.

 mass.win <- owin(poly=data.frame(x=rev(mass.map$x), y=rev(mass.map$y)))

Polygon contains duplicated vertices

Polygon is self-intersecting Error in owin(poly = data.frame(x = rev(mass.map$x), y = rev(mass.map$y))) : Polygon data contain duplicated vertices and self-intersection

Then I figured that maybe the polygon returned by map() is not meant to be fed to owin(). So I tried loading a massachusetts shape file (I am totally taking guesses at this point).:

x <- readShapePoly("../Geog/OUTLINE25K_POLY") ## The shape file for MASS, loaded from MassGIS website
mass.poly <- x <- readShapePoly("../Geog/OUTLINE25K_POLY", force_ring=T, delete_null_obj=T) ## I got following error whether or not I used force_ring

mass.owin <- as(mass.poly, "owin") Checking 1006 polygons...1, Polygon 1 contains duplicated vertices [Checking polygon with 91844 edges...] 2, 3, .. [etd 1:21:52] ....10 [etd 36:12] ..... [etd 23:10] ....20 [etd 16:59] ..... [etd 13:22] ....30 [etd 11:01] ..... [etd 9:21] ....40 [etd 8:06] ..... [etd 7:09] ....50 [etd 6:23] ..... [etd 5:46] ....60 [etd 5:15] ...[Checking polygon with 2449 edges...] .. [etd 4:49] ....70 [etd 4:27] ..... [etd 4:07] ....80 [etd 3:50] ..... [etd 3:36] ....90 [etd 3:22] ..... [etd 3:11] ....100 [ etc.

I got messages complaining about intersecting vertices, etc. and it failed to build the polygon.

Some context on problem: I am trying to use functions in spatstat for spatial relative risk calculations, ie, the spatial ratio of denstity of cases vs. controls. For that I need an observation window and point plot within that window. I could cheat and make the observation window a rectangle around massachusetts but that would presumably distort values near the coast. In any case, I'd like to learn how to do this right for any future work I do with this package. Thanks for any help you can provide.

Answer 1

EDIT 2021-02-04: I had this clockwise/anti-clockwise problem again and found my own answer the only one addressing the issue for spatstat. The answer was not very helpful. Have improved it to make it useful for a wider range of applications.

spatstat package wants owin object coordinates specified anticlockwise . A quote from the documentation of version 1.36-0:

single polygon: If poly is a matrix or data frame with two columns, or a structure with two component vectors x and y of equal length, then these values are interpreted as the cartesian coordinates of the vertices of a polygon circumscribing the window. The vertices must be listed anticlockwise. No vertex should be repeated (ie do not repeat the first vertex).

library("maps")
library ("sp")
library("spatstat")
mass.map <- map("state", "massachusetts:main", fill=T)

First, you'll need to find out whether your polygon is running clockwise or anticlock-wise. The approach here can be used to find out the answer. Formulate it as a function:

#' @title Check whether points for an owin are clockwise
#' @param x a dataframe with x coordinates in the first column and y coordinates in the second. 
#' @details Similarly to owin, the polygon should not be closed
#' @return A logical telling whether the polygon is arranged clockwise.
#' @author The idea has been scavenged from https://stackoverflow.com/a/1165943/1082004

clockwise <- function(x) {
    
  x.coords <- c(x[[1]], x[[1]][1])
  y.coords <- c(x[[2]], x[[2]][1])
  
  double.area <- sum(sapply(2:length(x.coords), function(i) {
    (x.coords[i] - x.coords[i-1])*(y.coords[i] + y.coords[i-1])
  }))
  
  double.area > 0
} 

Now, see whether the coordinates in mass.map are clockwise:

clockwise(data.frame(x=mass.map$x, y=mass.map$y))
#> TRUE

They are. Turn the coordinates anti-clockwise by usingrev function, which reverses vectors for x and y :

mass.win <- owin(poly=data.frame(x=rev(mass.map$x), y=rev(mass.map$y)))
plot(mass.win)

Answer 2

I'm quite familiar with the problem you have. If I understood right, you desire to get a polygonal object of class owin. Following codes will help you to acquire what you wanted.

#Loading the required packages
library (sp)
library(maps)

# Reading the dataset
mass.map <- map("state", "massachusetts:main", fill=T)

IDs <- sapply(strsplit(mass.map$names, ":"), function(x) x[1])
# converting can be done by loading the powerful package "maptools"
library(maptools)
# Converting into SpatialPolygons-object
mass.poly <- map2SpatialPolygons(mass.map, IDs = IDs)

# Converting by coercing into owin-object
mass.owin <- as.owin.SpatialPolygons(mass.poly)

Answer 3

The original question was posted 7 years ago (2014). The spatstat package has changed vastly since then.

The error messages about duplicated vertices and self-intersecting polygons do not occur anymore , because the code now automatically corrects these flaws in the polygon data.

The error message Area of polygon is negative - maybe traversed in wrong direction? still occurs . This is because owin requires polygon vertices to be listed in anticlockwise order around an outer boundary (and clockwise order around the boundary of a hole). If your window is a single polygon rather than a collection of polygons, the fix is to simply reverse the order of the coordinate vectors using rev :

library(maps)
library(sp)
library(spatstat)
mass.map <- map("state", "massachusetts:main", fill=TRUE)
mass.win <- owin(poly=lapply(mass.map, rev))

We can't make this happen automatically because it is not always what the user wanted.

For more information, see Chapter 3 of the spatstat book , which you can download for free from here .